Title :
Nonuniformity correction of infrared image sequences using the constant-statistics constraint
Author_Institution :
Comput. Neuroeng. Lab., Florida Univ., Gainesville, FL
fDate :
8/1/1999 12:00:00 AM
Abstract :
Using clues from neurobiological adaptation, we have developed the constant-statistics (CS) algorithm for nonuniformity correction of infrared focal point arrays (IRFPAs) and other imaging arrays. The CS model provides an efficient implementation that can also eliminate much of the ghosting artifact that plagues all scene-based nonuniformity correction (NUC) algorithms. The CS algorithm with deghosting is demonstrated on synthetic and real infrared (IR) sequences and shown to improve the overall accuracy of the correction procedure
Keywords :
image sequences; infrared imaging; statistical analysis; constant-statistics algorithm; constant-statistics constraint; correction procedure accuracy; deghosting; ghosting artifact elimination; imaging arrays; infrared focal point arrays; infrared image sequences; neurobiological adaptation; real infrared sequences; scene-based nonuniformity correction; synthetic infrared sequences; Adaptive arrays; Calibration; Gain measurement; Image sensors; Image sequences; Infrared imaging; Linear approximation; Optical imaging; Pixel; Statistics;
Journal_Title :
Image Processing, IEEE Transactions on